Array-based methods for analysing mixed samples using different allele-specific labels, in particular for detection of fetal aneuploidies

ABSTRACT

Provided includes methods and systems useful in array-based analysis of mixed nucleic acid populations, including for genotyping and copy number analysis of the various subpopulations of the mixed nucleic acid population. Also provided includes methods and systems useful in the diagnosis of genetic abnormalities in a mixed nucleic acid population taken from an organism.

RELATED APPLICATIONS

This application claims priority from U.S. provisional patentapplication No. 62/514,681, filed Jun. 2, 2017, which is herebyincorporated herein by reference in its entireties for all purposes.

BACKGROUND

This disclosure provides methods and systems useful in array-basedanalysis of mixed nucleic acid populations, including for genotyping andcopy number analysis of the various subpopulations of the mixed nucleicacid population. The disclosure also provides methods and systems usefulin the diagnosis of genetic abnormalities in a mixed nucleic acidpopulation taken from an organism. For example, disclosed herein aremethods and systems useful in the diagnosis of fetal geneticabnormalities or tumor genetic abnormalities using samples obtainednoninvasively from pregnant females or patients. Such samples caninclude mixed nucleic acid populations derived from blood, plasma,serum, urine, stool or saliva.

Analysis of mixed nucleic acid populations, for example DNA and RNAsamples obtained from a single tissue source such as blood, urine orsaliva but containing distinct nucleic acid subpopulations, has elicitedsignificant interest in the research and health care communities. Usingsuitable methods, mixed nucleic acid populations derived from cell-freeDNA (or RNA) taken from pregnant females can be analyzed to determinefetal characteristics, including disease inheritance. Similarly, mixednucleic acid populations derived from cell-free DNA (or RNA) taken fromcancer patients can be analyzed to determine various characteristicssuch as tumor malignancy, tumor origin or drug susceptibility. Whileanalysis of such mixed nucleic acid populations can be technicallycomplex due to the high degree of similarity between the varioussubpopulations, the difficulty of the analysis is outweighed by the easeof obtaining appropriate nucleic acid samples cheaply, quickly andnon-invasively through procedures such as phlebotomy or urine/salivacollection. One mode of analyzing cell-free DNA, nucleic acidsequencing, is informative but costly on a per-sample andtime-consuming. Microarray analysis is cheaper and quicker thansequencing, but current commercial embodiments of microarray products donot readily support discrimination between the different and highlysimilar subpopulations present in a mixed nucleic acid population. As aresult of the low concentration of fetal DNA in maternal samples, andlow concentration of tumor DNA in a blood sample containing circulatingtumor cells, single or low multiplex assays are unlikely todifferentiate between an aneuploid fetus (e.g., trisomy of chromosome21) from a euploid fetus, or a tumor cell from a healthy cell in acancer patient. For example, fetal DNA can be present at levels ofbetween 4%-15% of total cell-free DNA in blood; DNA derived from aparticular fetal chromosome would represent one-twenty-third of suchfetal DNA. Detection of a trisomy would require reliable detection ofsignal changes as low as 1-2% above background. Moreover, the analysisis further complicated by the limited amount of nucleic acid availablethrough non-invasive sampling methods. For example, a maternal sample of10 mls of whole blood can yield between 5 and 15 ng of purifiedcell-free DNA in a typical assay.

Due to the current challenges posed by such non-invasive approaches, amajority of pregnant women are subject to prenatal testing, includingmaternal serum screening and/or an ultrasound test, to determine risksfor common birth defects, such as those resulting from trisomy 13, 18,and 21. However, the sensitivity and specificity of such tests are verypoor leading to high false positive rates. As a result of the high falsepositive rates of such conventional tests, individuals typically mustconduct follow-up testing with an invasive diagnostic test, such asChorionic Villus Sampling (CVS) between 11 and 14 weeks gestation oramniocentesis after 15 weeks gestation. These invasive procedures carrya risk of a miscarriage of around one percent (see Mujezinovic andAlfirevic, Obstet. Gynecol., 110:687-694 (2011)). Current analysis offetal cells typically involves karyotyping or fluorescent in situhybridization (FISH) and does not provide information about single genetraits. As a result, additional tests are required for identification ofsingle gene diseases and disorders. Because prenatal diagnosis can becritical for management of a pregnancy with chromosomal abnormalitiesand localized genetic abnormalities, an accurate and early diagnosis isimportant to allow for interventional care before or during delivery andto prevent devastating consequences for the neonate.

Similarly, on the cancer front, powerful tools such as OncoScan® havebeen developed for purposes of diagnosing cancers. However, such samplesare typically biopsy samples taken in invasive procedures that are bothexpensive and potentially risky to the patient. Through the use ofmicroarray-based technology, researchers are able to identify largenumbers of Single Nucleotide Polymorphisms (SNPs) on a single array,which allows for the rapid and accurate detection of geneticabnormalities in a subject. As an example of one such product is the SNPdetection microarray product from Affymetrix called OncoScan®. TheOncoScan® product provides genome-wide copy number andloss-of-heterozygosity (LOH) profiles from solid tumor samples. Such atechnology is a powerful tool in cancer diagnostics because it helps toovercome significant challenge due to the difficulty of working withlimited amounts of DNA from highly degraded FFPE samples. See, forexample, U.S. Pat. No. 8,190,373. However, such technologies are findingapplication in numerous other fields, as well. Specifically, geneticabnormalities account for a wide number of pathologies, includingpathologies caused by chromosomal aneuploidy (e.g., Down syndrome),germline mutations in specific genes (e.g., sickle cell anemia), andpathologies caused by somatic mutations (e.g., cancer), and in manycases, the detection of such genetic abnormalities is complicated byinvasive diagnostic procedures.

As such, the development of a microarray based test that is sensitiveand specific enough to detect genetic abnormalities in samples obtainedby non-invasive means with low false-positive and false-negative rateswould be of benefit to the field of molecular diagnostics. Recently,Ariosa Diagnostics reported studies involving microarray based analysisof cell-free DNA from maternal blood to detect the presence of fetalaneuploidies. See, e.g., Stokowski et al., Prenatal Diagnosis35:1243-1246 (2015). Such methods involved analysis of bulk signals fromnon-polymorphic loci (i.e., loci that are expected to be identical forboth mother and fetus) to estimate chromosomal copy number by measuringfluctuations in total signal detected from both maternal and fetal DNAat a given genetic locus. This necessitates a design strategy wherebythe array is configured to interrogate non-polymorphic loci to determinecopy number of the underlying chromosomes.

Furthermore, at least in some cases use of polymorphic loci forestimating copy numbers has downstream benefits in the context oftesting for fetal aneuploidy because it preserves the possibility ofdetermining which parent contributed to the copy number variation.However, copy number analysis based on signals corresponding topolymorphic sites can be challenging and these challenges are magnifiedwhen analyzing samples from different populations.

There is a need to develop improved methods (as all as associatedcompositions, systems, devices and instruments) that leverages thehigh-throughput genotyping capabilities of microarray-based analysis togenerate data from a single set of interrogation sites (for example, adata from a single set of polymorphic loci in mixed DNA populations),which can then be used to both genotype and estimate copy number of agiven locus or chromosome within the major and minor DNA populationswithin mixed nucleic acid populations.

Described herein are methods and systems for analyzing a mixed nucleicacid sample to detect differences in copy number of a targetpolynucleotide, such as a detection of copy number variants indicatingchromosomal aneuploidy, as well as methods of genotyping such targetpolynucleotides even when present at low levels within a mixed nucleicacid population.

SUMMARY

One embodiment of the invention, in the context of a probe array, usessignals associated with first and second nucleotide variants present ina nucleic acid sample from an organism to measure copy numbers, thenucleic acid sample containing a mixed nucleic acid population. In oneembodiment, copy numbers (for example, of a chromosome and/or of achromosomal region and/or of a particular nucleotide sequence) aremeasured (e.g., estimated) with respect to a minor subpopulation withinthe mixed nucleic acid population of the nucleic acid sample. In oneembodiment, the nucleic acid sample is obtained from a pregnant motherand contains a major nucleic acid subpopulation corresponding to DNA ofthe mother and a minor subpopulation corresponding to fetal DNA. Inanother embodiment, the nucleic acid sample is obtained from anindividual with cancer or other tumors and the major nucleic acidsubpopulation corresponds to DNA from non-tumor cells and the minorsubpopulation corresponds to DNA from tumor cells. Some embodiments ofthe invention are also applicable to various other contexts in whichmeasurement of copy numbers is desired for a nucleic acid samplecontaining a mixed nucleic acid population including at least a majorsubpopulation and a minor subpopulation.

In a particular embodiment of the invention, signals corresponding toprobes hybridized to nucleotide variants associated with polymorphicsites are used to measure copy numbers of a minor subpopulation of amixed nucleic acid population in a nucleic acid sample obtained from anorganism.

In some alternative embodiments, a probe array comprises a plurality ofprobes for polymorphic sites usable for measuring potential copy numbervariations in samples and signals from a pre-selected subset of theplurality of probes are used to estimate fetal fraction (or, in otherembodiments, the fraction of another type of subpopulation associatedwith a sample), the preselected subset of probes having been selectedbased on performance of the probes with a model used to predict allelefrequency from signal values.

In some embodiments of the invention, reference signal values that aregenotype specific for a polymorphic locus are used for detecting copynumber variations.

Certain aspects and various embodiments of the disclosure can be furtherdescribed by the following enumerated clauses:

1. A method for detecting a copy number in a fetus, comprising:obtaining a biological sample from a subject who is a pregnant female,the biological sample including nucleic acid of both maternal and fetalorigin containing a target nucleic acid sequence located on a firstchromosome, the target nucleic acid sequence containing a polymorphicsite for a single nucleotide polymorphism (SNP); generating a populationof nucleic acid fragments containing or derived from the target nucleicacid sequence; conducting a first assay comprising (a) contacting thepopulation of nucleic acid fragments with an oligonucleotide arraycontaining a first oligonucleotide probe configured to hybridize to thetarget nucleic acid sequence containing the polymorphic site of the SNP;and (b) detecting, using a detector, first signals indicatinghybridization of the oligonucleotide probe to one or more nucleic acidfragments of the population containing a first allelic variant (“Aallele”) of the SNP and second signals indicating hybridization of theoligonucleotide probe to one or more nucleic acid fragments of thepopulation containing a second allelic variant (“B allele”) of the SNP;and determining, using the first signals and the second signals, any oneor more of the following: (i) the copy number of the first chromosome inthe fetus; (ii) a fetal genotype for the SNP; (iii) a maternal genotypefor the SNP; and (iv) a fetal fraction of the sample.

2. The method of clause 1, further comprising calculating the observedB-allele frequency (BAF) for the allelic variants of the SNP present inthe sample.

3. The method of clause 2, further including calculating the fetalfraction of the sample using the BAF.

4. The method of clause 1, wherein the polymorphic site of the SNP canbe homozygous for the A allele (“AA”), homozygous for the B allele(“BB”) or heterozygous (“AB”).

5. The method of clause 4, wherein the detector has a first and a seconddetection channel, and the genotyping further includes detecting thefirst signals in the first channel and the second signals in the secondchannel.

6. The method of clause 5, wherein the first signals in the firstchannel indicate the amount of A allele present in the nucleic acidpopulation and the second signals indicate the amount of B allelepresent at nucleic acid population.

7. The method of clause 6, wherein determining the copy number of thefirst chromosome in the fetus comprises determining a ratio of a firstvalue to a second value.

8. The method of clause 7, further comprising calculating the firstvalue by normalizing and summarizing the first signals to obtain a firstnormalized and summarized signal value, normalizing the second signalsto obtain a normalized and summarized second signal value, and addingthe normalized and summarized first signal value to normalized andsummarized second signal value to obtain the first value.

9. The method of clause 4, further including determining a firstmaternal SNP genotype.

10. The method of clause 8, wherein the second value is obtained by:conducting the first assay on additional biological samples serving asreference samples and identifying reference samples having an SNPgenotype corresponding to the first maternal SNP genotype; fromconducting the first assay on the reference samples, obtaining firstsignals reference signals detected in the first channel indicating anamount of A allele present in the polymorphic site of the SNP withrespect to the additional biological samples and obtaining secondreference signals indicating the amount of B allele present at thepolymorphic site.

11. The method of clause 10 wherein the additional biological samplesare from non-pregnant individuals.

12. The method of clause 10 wherein the additional biological samplesinclude some samples from pregnant females and some samples fromnon-pregnant individuals.

13. The method of clause 10 wherein the additional biological samplesinclude samples from pregnant females assayed on the sameoligonucleotide array as the biological sample from the subject pregnantfemale.

14. The method of clause 1, wherein the nucleic acid sample includesmaternal blood, plasma or serum and the nucleic acid of both maternaland fetal origin includes cell-free DNA (cfDNA).

15. The method of clause 1, wherein the fetal DNA is about 30% of totalDNA in the nucleic acid sample.

16. The method of clause 1, wherein the fetal DNA is no greater than 30%of total DNA in the nucleic acid sample.

17. The method of clause 1, wherein the fetal DNA is more than 30% oftotal DNA in the nucleic acid sample.

18. The method of clause 1, wherein the fetal DNA is no greater than 20%of total DNA in the nucleic acid sample.

19. The method of clause 1, wherein the fetal DNA is no greater than 15%of total DNA in the nucleic acid sample.

20. The method of clause 1, wherein the fetal DNA is no greater than 10%of total DNA in the nucleic acid sample.

21. The method of clause 1, wherein the fetal DNA is no greater than 5%of total DNA in the nucleic acid sample.

22. The method of clause 1, wherein the fetal DNA is no greater than 15%and no less than 1% of total cell free DNA in the nucleic acid sample.

23. The method of clause 1, wherein the fetal DNA is no less than 30% oftotal cell free DNA in the nucleic acid sample.

24. A method for analyzing a mixed nucleic acid sample obtained from anorganism, comprising: obtaining or deriving from an organism a nucleicacid sample containing a mixed nucleic acid population that includes amajor subpopulation and a minor subpopulation, the major and minorsubpopulations each including a target sequence located in a firstchromosomal region and containing a polymorphic site, wherein thepolymorphic site can include any combination of a first nucleotidevariant and a second nucleotide variant; genotyping the polymorphicsite, wherein the genotyping includes: (a) hybridizing at least onenucleic acid fragment derived from the mixed nucleic acid population andcontaining the polymorphic site to an oligonucleotide probe of anoligonucleotide array; and (b) detecting from the oligonucleotide array,using a detector, a first signal indicating the presence or absence ofthe first nucleotide variant (“A signal”) and a second signal indicatingthe presence or absence of the second nucleotide variant (“B signal”).

25. The method of clause 24, further including determining the copynumber of the first chromosomal region in the minor subpopulation usingthe first signal and the second signal.

26. The method of clause 24, further including determining the copynumber of the first chromosomal region in the major subpopulation usingthe first signal and the second signal.

27. The method of clause 24, further including determining the genotypeof the polymorphic site for the minor subpopulation using the firstsignal and the second signal.

28. The method of clause 24, further including determining the genotypeof the polymorphic site for the major subpopulation using the firstsignal and the second signal.

29. The method of clause 24, further including determining the relativeamounts of the major subpopulation and the minor subpopulation in themixed nucleic acid population using the first signal and the secondsignal.

30. The method of any of the preceding clauses, wherein the majorsubpopulation and the minor subpopulation original from differentsources in the organism.

31. The method of clause 24, wherein the detector includes a firstdetection channel and a second detection channel, and further includingthe steps of detecting the first signal in the first detection channeland the second signal in the second detection channel.

32. The method of any of the preceding clauses, wherein the mixednucleic acid population includes cell-free DNA.

33. The method of clause 30, wherein the cell-free DNA is obtained orderived from the organism's blood, plasma, serum, urine, stool orsaliva.

34. The method of any of the preceding clauses, wherein the organismincludes a tumor, the major subpopulation includes or is derived fromnormal tissue and the minor subpopulation includes or is derived fromthe tumor.

35. The method of any of the preceding clauses, wherein the organism isa pregnant female, the mixed nucleic acid population is cell-freenucleic acid obtained from the female's blood, the major subpopulationis maternal nucleic acid and the minor subpopulation includes or isderived from fetal nucleic acid.

36. The method of clause 35, wherein the minor subpopulation includesfetal DNA present at no greater than 40% of total DNA in the nucleicacid sample.

37. The method of clause 35, wherein the fetal DNA is no greater than25% of total DNA in the nucleic acid sample.

38. The method of clause 35, wherein the fetal DNA is no greater than15% of total DNA in the nucleic acid sample.

39. The method of clause 35, wherein the fetal DNA is no greater than 5%of total DNA in the nucleic acid sample.

40. The method of clause 35, wherein the fetal DNA is no greater than15% and no less than 1% of total cell free DNA in the nucleic acidsample.

41. The method of any of the preceding clauses, wherein the mixednucleic acid population contains or is derived from cell-free DNApresent in blood of the organism at concentration of no greater than 5ng/ml and no less than 0.1 ng/ml.

42. The method of clause 24, wherein the amount of mixed nucleic acidpopulation used is no greater than 50 ngs, 40 ngs, 30 ngs, 15 ngs, 10ngs, 5 ngs, 3 ngs or 1 ng.

43. The method of clause 24 or 35, wherein the polymorphic site includesa bi-allelic SNP, the first nucleotide variant is a first allelicvariant of the SNP (“A allele”) and the second nucleotide variant is asecond allelic variant of the SNP (“B allele”).

44. The method of clause 43, wherein the bi-allelic SNP that can includeone or both of the first allelic variant (“A allele”) or the secondallelic variant (“B allele”), and wherein the SNP genotype can behomozygous for the A allele (“AA”), homozygous for the B allele (“BB”)or heterozygous (“AB”).

45. The method of clause 43, further including calculating the observedB-allele frequency (BAF) for the SNP in the nucleic acid sample.

46. The method of clause 45, further including calculating the fetalfraction of the sample using the BAF.

47. The method of clause 24 or 35, wherein the first signal indicatesthe amount of A allele present in the polymorphic site and the secondsignal indicates the amount of B allele present at the polymorphic site.

48. The method of clause 24, 35 or 47, wherein the organism is apregnant female, and wherein the method further includes determining thecopy number of the first chromosomal region in the fetus by determininga ratio of a first value to a second value.

49. The method of clause 48, further including calculating the firstvalue by adding the first signal, or a normalized value thereof, and thesecond signal, or a normalized value thereof.

50. The method of clause 49, further including determining a firstmaternal SNP genotype using the first signal and the second signal.

51. The method including performing the method of clause 46 using one ormore additional biological samples from pregnant females and identifyinga subset of additional biological samples having a SNP genotypecorresponding to the first maternal SNP genotype, and obtaining a secondvalue by taking sums of the A signal and the B signal from eachadditional sample in the subset of additional biological samples andobtaining a medium of the sums as the second value.

52. The method of clause 24, 34 or 35, wherein the polymorphic siteincludes a nucleotide mutation, the first nucleotide variant is themutant version of the target nucleic acid sequence and the secondnucleotide variant is the wild-type version of the polymorphic site, theA signal indicates the amount of the mutant version and the B signalindicates the amount of wild-type version in the sample.

53. A system for use in detecting copy number variation in a nucleicacid sample, the system comprising: a probe microarray; a scanner; aprocessor; and a memory encoded with instructions for carrying outprocessing referenced in any one of clauses 1-52 above.

54. A computer program product in a non-transitory computer readablemedium storing instructions for carrying out processing referenced inany one of clauses 1-53 above.

These and other various embodiments are disclosed in further detailbelow and in the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a sample processing system in accordance with anembodiment of the present invention.

FIG. 2 illustrates a high-level block diagram of reference sampleprocessor implemented by the system of FIG. 1 in accordance with anembodiment of the present invention.

FIG. 3 illustrates a high-level block diagram of subject sampleprocessor implemented by the system of FIG. 1 in accordance with anembodiment of the present invention.

FIG. 4 illustrates a reference sample processing method in accordancewith an embodiment of the present invention.

FIG. 5 illustrates a subject sample processing method in accordance withan embodiment of the present invention.

FIG. 6 illustrates an exemplary computer system configurable by acomputer program product to carry out embodiments of the presentinvention.

While the invention is described with reference to the above drawings,the drawings are intended to be illustrative, and other embodiments areconsistent with the spirit, and within the scope, of the invention.

DETAILED DESCRIPTION

The various embodiments now will be described more fully hereinafterwith reference to the accompanying drawings, which form a part hereof,and which show, by way of illustration, specific examples of practicingthe embodiments. This specification may, however, be embodied in manydifferent forms and should not be construed as limited to theembodiments set forth herein; rather, these embodiments are provided sothat this specification will be thorough and complete, and will fullyconvey the scope of the invention to those skilled in the art. Amongother things, this specification may be embodied as methods or devices.Accordingly, any of the various embodiments herein may take the form ofan entirely hardware embodiment, an entirely software embodiment or anembodiment combining software and hardware aspects. The followingspecification is, therefore, not to be taken in a limiting sense.

As used in this application, the singular form “a,” “an,” and “the”include plural references unless the context clearly dictates otherwise.For example, the term “an agent” includes a plurality of agents,including mixtures thereof.

All references cited herein are incorporated herein in their entiretiesfor all their purposes. To the extent any reference includes adefinition or uses a claim term in a manner inconsistent with thedefinitions and disclosure set forth herein, the definitions anddisclosure of this application will control.

Disclosed herein are methods (as well as associated systems, apparatusesand software) for performing array-based analysis of mixed nucleic acidpopulations. The array or microarray optionally comprises a support,preferably solid, with nucleic acid probes attached to the support.Preferred arrays typically comprise a plurality of different nucleicacid probes that are coupled to a surface of a substrate in different,known locations. These arrays, also described as “microarrays” orcolloquially “chips” have been generally described in the art, forexample, U.S. Pat. Nos. 5,143,854, 5,445,934, 5,744,305, 5,677,195,5,800,992, 6,040,193, 5,424,186 and Fodor et al., Science, 251:767-777(1991). Each of which is incorporated by reference in its entirety forall purposes. The probes can be of any size or sequence, and can includesynthetic nucleic acids, as well as analogs or derivatives ormodifications thereof, as long as the resulting array is capable ofhybridizing under any suitable conditions with a nucleic acid samplewith sufficient specificity as to discriminate between different targetnucleic acid sequences of the sample. In some embodiments, the probes ofthe array are at least 5, 10 or 20 nucleotides long. In someembodiments, the probes are no longer than 25, 30, 50, 75, 100, 150, 200or 500 nucleotides long. For example, the probes can be between 10 and100 nucleotides in length.

In some embodiments, the array is capable of genotyping nucleic acidmolecules in the mixed nucleic acid population. In some embodiments, tothe determination of the nucleic acid sequence information from anucleic acid sample at one or more nucleotide positions. The nucleicacid sample may contain or be derived from any suitable source,including the genome or the transcriptome. In some embodiments,genotyping may comprise the determination of which allele or alleles anindividual carries at one or more polymorphic sites. For example,genotyping may include or the determination of which allele or allelesan individual carries for one or more SNPs within a set of polymorphicsites. For example, a particular nucleotide in a genome may be an A insome individuals and a C in other individuals. Those individuals whohave an A at the position have the A allele and those who have a C havethe B allele. In a diploid organism the individual will have two copiesof the sequence containing the polymorphic position so the individualmay have an A allele and a B allele or alternatively two copies of the Aallele or two copies of the B allele. Those individuals who have twocopies of the B allele are homozygous for the B allele, thoseindividuals who have two copies of the A allele are homozygous for the Ballele, and those individuals who have one copy of each allele areheterozygous. The array may be designed to distinguish between each ofthese three possible outcomes. A polymorphic location may have two ormore possible alleles and the array may be designed to distinguishbetween all possible combinations. In some embodiments, genotypingincludes detecting a single nucleotide mutation that arisesspontaneously in the genome, amongst a background of wild-type nucleicacid. In some embodiments, genotyping includes determining fetal bloodtype from a sample of maternal blood or diagnosing cancer from a sampleof human or animal blood.

A polymorphism can occur when there exist two or more geneticallydetermined alternative sequences in a population. The alternativesequences can include alleles (e.g., naturally occurring variants) orspontaneously arising mutations that only occur in one or few individualorganisms. A polymorphic site is formed by nucleic acid position(s) atwhich a difference in nucleic acid sequence occurs. A polymorphism maycomprise one or more base changes, an insertion, a repeat, or adeletion. A polymorphic locus may be as small as one base pair.Polymorphic sites include restriction fragment length polymorphisms,variable number of tandem repeats (VNTR's), hypervariable regions,minisatellites, dinucleotide repeats, trinucleotide repeats,tetranucleotide repeats, simple sequence repeats, and insertionelements. The first identified variant or allelic form is arbitrarilydesignated as the reference form and other variant or allelic forms aredesignated as alternative or variant or mutant alleles. The variant orallelic form occurring most frequently in a selected nucleic acidpopulation is sometimes referred to as the wildtype form. In someembodiments, the wildtype form can be referred to as a “majorsubpopulation” and the mutant can be referred to as ta “minorsubpopulation”. In some embodiments, the more frequently occurringallele can be referred to as a “major subpopulation” and the rarer orless frequently occurring allele can be referred to as ta “minorsubpopulation”. Diploid organisms may be homozygous or heterozygous forallelic forms. A diallelic polymorphism has two forms. A triallelicpolymorphism has three forms. A polymorphism between two nucleic acidscan occur naturally, or be caused by exposure to or contact withchemicals, enzymes, or other agents, or exposure to agents that causedamage to nucleic acids, for example, ultraviolet radiation, mutagens orcarcinogens. SNPs are positions at which two alternative bases occur atappreciable frequency (>1%) in the human population, and are the mostcommon type of human genetic variation.

The following passages describe various embodiments of methods toanalyze mixed nucleic acid populations and to determine the genotypeand/or copy number of specific genetic loci present within differentsubpopulations (e.g., major and minor subpopulations) of the mixednucleic acid population.

In some embodiments, a sample includes a mixed nucleic acid populationfrom different subpopulations (e.g., major and minor subpopulations). Inone embodiment, a sample contains a mixture of maternal nucleic acids (amajor subpopulation) and fetal nucleic acids (a minor subpopulation.) Inone embodiments, the nucleic acids from each subpopulation are cell-freeDNA. In some embodiments, the amount of the fetal DNA in a sample rangesfrom about 1% to about 50% of the total amount of DNA in the sample. Insome embodiments, the amount of the fetal DNA in the sample is about 1%,about 5%, about 10%, about 15%, about 20%, about 25%, about 30%, about35%, about 40%, about 45% or about 50% of the total amount of DNA in thesample, or any intervening amount of the foregoing. In some embodiments,the amount of the fetal DNA in the sample is no greater than about 1%,about 5%, about 10%, about 15%, about 20%, about 25%, about 30%, about35%, about 40%, about 45% or about 50% of the total amount of DNA in thesample, or any intervening amount of the foregoing. In some embodiments,the amount of the fetal DNA in the sample is more or no less than about1%, about 5%, about 10%, about 15%, about 20%, about 25%, about 30%,about 35%, about 40%, about 45% or about 50% of the total amount of DNAin the sample, or any intervening amount of the foregoing.

In some embodiments, the mixed nucleic acid population in a sample thatcan be processed according to various methods disclosed herein includescell-free DNA from major and minor sources. In some embodiments, themixed nucleic acid population is circulating DNA isolated from wholeblood, plasma, serum or some other bodily fluid. In some embodiments,the mixed nucleic acid population includes maternal and fetal cell-freeDNA. In some embodiments, the amount of mixed nucleic acid population ina sample is in the range from one or more nanograms (ngs) to about oneor more milligrams (mgs). In some embodiments, the amount mixed nucleicacid population is about 1 ng, about 3 ngs, about 5 ngs, about 10 ngs,about 15 ngs, about 30 ngs, about 40 ngs, about 50 ngs, about 100 ngs,about 150 ngs, about 300 ngs, about 400 ngs, about 500 ngs, about 1 mg,about 3 mgs, about 5 mgs or more, or any intervening amount of theforegoing. In some embodiments, the amount of the mixed nucleic acidpopulation used is no greater than about 50 ngs, about 40 ngs, about 30ngs, about 15 ngs, about 10 ngs, about 5 ngs, about 3 ngs or about 1 ng.In some embodiments, the amount mixed nucleic acid population is aboutor less than about 50 ngs, about 40 ngs, about 30 ngs, about 15 ngs,about 10 ngs, about 5 ngs, about 3 ngs or about 1 ng.

In some embodiments, a sample that is processed according to variousmethods disclosed herein includes a mixed nucleic acid populationderived from one or more of whole blood, plasma, serum, urine, stool orsaliva. In some embodiments, a mixed nucleic acid population can bederived from blood. In some embodiments, blood, e.g., whole blood can befurther processed to provide plasma and/or serum from which a mixednucleic acid population for a sample is prepared.

In some embodiments, the disclosed methods (as well as relatedcompositions, kits and systems) are useful in detecting genetic changesin small amounts of whole blood, plasma, serum or other bodily fluid.For example, the amount of bodily fluid (e.g., whole blood, plasma,serum or saliva) that is used to prepare a mixed nucleic acid populationof a sample can be in the range of about 0.1 to several milliliters(mls). In some embodiments, the amount of whole blood, plasma, serum orother bodily fluid that is used to prepare a mixed nucleic acidpopulation is about 0.1 ml, about 0.25 ml, about 0.5 ml, about 0.75 ml,about 1 ml, about 1.5 ml, about 2 mls, about 2.5 mls, about 3 mls, about3.5 mls, aout 4 mls, about 4.5 mls, about 5 mls about 5.5 mls, about 6mls, about 6.5 mls, abouyt 7 mls, about 7.5 mls, about 8 mls, about 8.5mls, about 9 mls, about 9.5 mls, or about 10 mls, or any interveningvolumes of the foregoing.

In some embodiments where whole blood is used to provide a mixed nucleicacid population of a sample, the amount of blood is about or less than0.1 ml, 0.25 ml, about 0.5 ml, about 0.75 ml, about 1 ml, about 1.5 ml,about 2 mls, about 2.5 mls or about 3 mls. In some embodiments, theamount of blood is no greater than about 0.25 ml, about 0.5 ml, about0.75 ml, about 1 ml, about 1.5 ml, about 2 mls, about 2.5 mls or about 3mls.

In some embodiments where plasma or serum is used to provide a mixednucleic acid population of a sample, the amount of plasma or serum isabout or less than 0.1 ml, 0.25 ml, about 0.5 ml, about 0.75 ml, about 1ml, about 1.5 ml, about 2 mls, about 2.5 mls or about 3 mls. In someembodiments, the amount of plasma or serum is no greater than about 0.25ml, about 0.5 ml, about 0.75 ml, about 1 ml, about 1.5 ml, about 2 mls,about 2.5 mls or about 3 mls.

FIG. 1 illustrates a sample processing system 2100 in accordance with anembodiment of the present invention. The system includes an arraycontaining probes specific for polymorphic loci in chromosomes ofinterest (e.g., chromosomes 13, 18, 21, X and Y) as well asrepresentative reference chromosomes (e.g., chromosomes 1 and 5) thatare assumed to be diploid. Different probes at different sites on thearray are configured to selectively hybridize to allele-specificextension products that are generated prior to hybridization to thearray, different allele-specific extension products will thereforehybridize to different sites on the array even though they differ by aslittle as one nucleotide. The hybridized allele-specific products arethen treated in order to generate a detectable signal in proportion tothe amount of hybridized product present. This-signal-generatingtreatment process is performed according to procedures outlined in theAxiom 2.0 Manual provided with the Axiom 2.0 reagent kit (catalog#901758). Signals emanating from the array were detected and analyzed asdescribed in the following passages.

Sample processing system comprises probe array 2101, scanner 2102, andcomputer 2103 which is configurable by computer program 2104 to processdata received from scanner 2102. Those skilled in the art willappreciate that various other components of a sample processing systemsuch as system 2100 would be present but are not separately illustratedherein including, for example, a fluid handling system for handlingvarious fluids (including, for example, biological samples to be placedin contact with probe array 2101, various washes, buffers, and otherfluids), and an autoloader for handling and transport of one or moreprobe arrays such as probe array 2101 including positioning probe arraysfor interaction with a fluid handling system and with scanner 2102.

In one embodiment, probe array 2101 is optimized for use in analyzingbiological samples taken from a pregnant female. In a particularembodiment, probe array 2101 comprises probes for a plurality ofpolymorphic sites on one or more chromosomes, each polymorphic siteassociated with a single nucleotide polymorphism. In some embodiments,probe array 2101 comprises probes corresponding to: 10,867 or moreunique SNPs on chromosomes 1 & 5; 7,559 or more unique SNPs onchromosome 13; 4,855 or more unique SNPs on chromosome 18; 2,083 or moreunique SNPs on chromosome 21; 1,0661 unique SNPs on chromosome X; and593 unique SNPs on chromosome Y. In one embodiment, the probe arrayincludes approximately 2-50 or more replicate probes corresponding toeach SNP. In some embodiments, where array space constraints limit theability to have both a large number of probes and a large number ofreplicates, results are improved by having a smaller number ofreplicates (e.g., 2-6) so that a larger number of unique probes (fordifferent polymorphic loci) can fit on an array of comparable size. Onepossible implementation (for illustrative purposes only) in whichreplicate numbers are relatively low (2 replicates for some probes and 6replicates for others) and numbers of unique probes are relatively highfor a given size probe array is shown in TABLE I below:

TABLE I Number of unique Number of unique probes with 2 replicatesprobes with 6 replicates Chrm per unique probe per unique probe Total 1& 5 1,233 9,634 10,867 13 1,322 6,237 7,559 18 518 4,337 4,855 21 2641,819 2,083 X 0 8,661 (+an additional 10,661 2000 with 4 replicates) Y 0 592 593

In alternative embodiments, the above numbers can be variedsignificantly without departing from an embodiment in which the numberof unique probes is maximized relative to array space while still havingsome replicate probes on the array.

FIG. 2 and FIG. 3 illustrate block diagrams of reference and subjectsample signal processing systems for implementing exemplary embodimentsof the invention. FIG. 4 and FIG. 5 show detailed processing methodsthat, in accordance with exemplary embodiments of the invention, arecarried out by the reference and subject signal processing systems ofFIG. 2 and FIG. 3. The systems and methods of FIGS. 2-5 can beimplemented on a computer such as computer 2103 of FIG. 1. In somealternative embodiments, those systems and methods can be implemented bya network of computers in communication with computer 2103. In suchalternatives, all or part of a computer program product storinginstructions for executing embodiments of the invention might be storedon remote network computers rather than on an end user computer.

FIG. 2 illustrates reference sample processor 2200. Processor 2200includes various processing modules for processing signal data fromreference samples in accordance with an embodiment of the invention. Theparticular elements shown in FIG. 2 are not necessarily all required invarious alternative embodiments of the invention. Also, in alternatives,the particular elements and, in some cases, the arrangement of thoseelements, can be varied from that shown.

As will be discussed further in the context of other figures below, insome embodiments, portions of reference processor 2200 can be used forprocessing a plurality of subject samples wherein the subject samplesare also used as reference samples. However, for clarity of illustrationand explanation, reference processor 2200 is described in the context ofprocessing reference samples only.

Data repository 2207 stores signal files generated from scanning probearrays to which reference samples have been introduced and selectivelyhybridized. Probe signal processing module 2201 receives and processessignals received from repository 2207. Module 2201 normalizes andsummarizes the signals as will be explained further in the context ofFIGS. 4-5. Genotyping module 2202 uses the normalized and summarizedsignal values to perform genotyping to provide genotypes for eachreference sample with respect to each SNP. Module 2203 creates modelreference signals for each genotype of each SNP and stores them inreference signal repository (e.g., a data file) 2208.

Module 2204 uses genotyping data from module 2202 to create modelsrelating signal values to copy numbers for each of two signal channels(as will be further described in the context of FIG. 4). Module 2205computes B-allele frequency (“BAF”) for each marker in each referencesample using the models generated by module 2204. Using the knownreference copy number data retrieved from data repository 2209, BAFvalues corresponding to the same A and B allele copy numbers and samemarker across reference samples are compared to each other and/or to theBAF value computed from the known copy number. Based on that comparison,module 2205 identifies the markers where B-allele frequencies computedfrom signals are most predictive of actual allele copy numbers and savesthem in fetal fraction marker selection repository 2211. The identifiedmarkers are saved for later use in determining fetal fraction in subjectmaternal samples (e.g., pregnant female patient samples).

Module 2206 processes signals for individual reference samplesindividually to compute log ratios relative to the reference signalsstored in repository 2208. Module 2206 stores the results in referencelog ratio repository 2210.

FIG. 3 illustrates subject sample processor 2300. Processor 2300includes various processing modules for processing signal data fromsubject (e.g., patient) samples in accordance with an embodiment of theinvention. The particular elements shown in FIG. 3 are not necessarilyall required in various alternative embodiments of the invention. Also,in alternatives, the particular elements and, in some cases, thearrangement of those elements, can be varied from that shown.

Data repository 2307 stores signal files generated from scanning probearrays to which subject samples have been introduced and selectivelyhybridized. Probe signal processing module 2301 receives and processessignals received from repository 2307. Module 2301 carries out the sameprocessing as module 2201 as will be explained further in the context ofFIGS. 4-5. Genotyping module 2302 uses the normalized and summarizedsignal values received from module 2301 to perform genotyping to providegenotypes for each subject sample with respect to each SNP.

The illustrated embodiment includes module 2303 which uses signals froma plurality of subject samples processed on a same sample plate tocreate model reference signals for each genotype of each SNP and module2303 stores them in reference signal repository (e.g., a data file)2308. Note that, in some embodiments, model reference signals obtainedfrom a prior reference assay have been previously determined by areference processor such as processor 2200 illustrated in FIG. 2. Insuch alternatives, a subject sample processor such as processor 2300would not necessarily require a separate model reference signaldetermination module such as module 2303 of FIG. 3. However, usingsubject samples to create model reference samples has the benefit ofminimizing effects that might otherwise be attributable to theparticular sample plate characteristics and/or assay conditions if thereference data is obtained from a different sample plate assayed at anearlier time.

Module 2304 uses genotyping data from module 2302 and marker-specificmodels from module 2204 relating A-signals to A-allele copy numbers andB-signals to B-allele copy numbers to convert A-signal values to A-copynumbers and B-signal values to B-copy numbers and then calculates theB-allele frequency (BAF) for each marker. As will be described in moredetail in the context of FIG. 5, fetal fraction calculator 2305calculates an estimated fetal fraction using the distribution of BAFvalues.

Fetal fraction analyzer 2309 determines whether the sample hassufficient fetal fraction to be used for evaluating aneuploidy. If so,then, fetal fraction analyzer 2309 uses the fetal fraction to updatereference values for expected signals in view of the fetal fractionestimate, as will be further described in the context of FIG. 5.

Module 2306 processes an individual subject sample to obtain log ratiosfor a signal corresponding to each marker relative to an appropriatereference signal and stores the log ratios in repository 2310.Specifically, module 2306 uses a reference signal corresponding to thedetermined genotype of the major subpopulation (for example, thegenotype of the maternal DNA) for that marker (as will be furtherdescribed in the context of FIG. 5) to obtain a log ratio value for thesubject's signal value for that marker relative to a reference value. Ina preferred embodiment, the estimated fetal fraction is used todetermine the expected signal threshold for an abnormal log ratio.However, in an alternative embodiment, a determined fetal fraction isnot necessarily used to determine the expected signal for an abnormallog ratio; rather, anything not commensurate with a normal log ratio canbe used.

Module 2311 analyzes the log ratio values to determine whetherthresholds are met for calling aneuploidy.

FIG. 4 illustrates reference sample processing method 2400. In oneembodiment, method 2400 is executed by reference processor 2200 of FIG.2. The particular steps shown in FIG. 4 are not necessarily all requiredin various alternative embodiments of the invention. Also, inalternatives, the particular steps and, in some cases, the order, can bevaried from that shown.

Step 2401 creates signal data files using signal data received fromscanner 2102 (shown in FIG. 1). Scanner 2102 detects probe signals intwo different channels for each marker, a first channel corresponding tothe A-allele of that marker and a second channel corresponding to theB-allele of that marker. In this embodiment, probes are designed to bemarker specific, but are detectable in different channels depending onwhich allele (A or B) of the marker the probe has hybridized to. Notethat, in alternative embodiments, different probes for each allele of amarker may be used.

Steps 2402-2404 perform initial probe signal processing.

Specifically, step 2402 applies generic signal covariate adjusternormalizing to the signals. In one embodiment, this processingnormalizes the signals with respect to variables such as, for example,guanine and cytosine content (GC content) and probe fragment length.Step 2403 applies quantile normalization. Step 2404 summarizes replicateprobe values. In one example, this comprises determining, for eachmarker with respect to each reference sample, a median signal value forall replicate probes hybridized to the A-allele (A-signal) and a mediansignal value for all replicate probes hybridized to the B-allele(B-signal).

Step 2405 genotypes each reference sample with respect to each marker.Step 2409 then creates a reference signal corresponding to each of thethree possible genotypes of each marker as follows: For a first marker,a first reference sample's A-signal for that marker is added to thefirst reference sample's B-signal for that marker to obtain a combinedA+B signal for the first marker with respect to the first reference.This is repeated for all other reference samples with respect to thefirst marker. Then, the median signal for the first marker across allreferences with a particular genotype is determined. For example, formarker1, the median signal value (A+B) for all references who have an AAgenotype for that marker is stored as a reference signal. Similarly, formarker1, the median signal value (A+B) for all references who have a BBgenotype for that marker is stored as a separate reference signal. And,for marker1, the median signal value (A+B) for all references who havean AB genotype is stored. This is repeated for each marker interrogatedby the probe array. An example of normalized reference signals (A+B)determined in this manner for three different markers in chromosome 1 isshown below in Table II:

TABLE II Median for Median for Median for AA genotype BB genotype ABgenotype reference reference reference Marker Chrm samples samplessample tag002626 1 984.0628318 745.1495922 864.2744595 tag002753 1660.4613573 969.9901649 756.9943685 tag002806 1 1128.81335 973.3259848988.8751251

In some embodiments, log ratios can be calculated and further processedat steps 2410, 2412, 2413, 2415, and 2411 for each reference sample asfollows. Step 2410, for each reference sample, determines a log ratiofor each marker as a log ratio of the reference sample's signal for thatmarker to the appropriate median reference signal (e.g., such as thosevalues in Table II above) depending on whether the reference sample hasbeen genotyped as AA, BB, or AB for that marker. Step 2412 appliesgeneric log ratio covariate normalizing to the log ratios. Step 2413optionally applies median autosome normalization on a per sample basis.Specifically, if the median of the median log ratios across allchromosomes is not 0 for a given sample, then all values are adjusted bythe increment needed to make the median of medians 0. Step 2415optionally applies a plate adjustment by applying median autosomenormalization again, but this time across all samples on the plate,applying an appropriate incremental adjustment as needed to make themedian of medians 0. Step 2411 summarizes each reference sample bychromosome or by some other unit of interest. In one embodiment, thisunit can be a chromosome arm, or a smaller or longer region of interest.In one embodiment, this is done by taking the median of all log ratiosfor all markers on a given chromosome as the summarized value for thatchromosome for a given sample. In alternative embodiments, an average orother methods of summarizing might be used. Step 2414 stores normalizedlog ratios results for each reference sample.

Steps 2406-2408 are used to select particular markers that are preferredfor use in determining fetal fraction of a subject sample. Markers forwhich a good ability to predict B-allele frequency for at least one ofthe homozygous genotypes is demonstrated are selected.

Step 2406 uses summarized signals from step 2404 and genotypes from step2405 to create a model relating signal value to copy number for eachallele of each marker. In one embodiment, the model is a linear model.In another embodiment the model is non-linear such as, for example, aLangmuir model. One method for creating a linear model is now describedin further detail. However, the described method can of course be variedin alternative embodiments.

In one embodiment, two models, an A-model and a B-model, are created forall autosomal markers where each of the three possible genotypes isrepresented by at least two reference samples. The A-model relatesA-signal value to A-copy number and the B-model relates B-signal valueto B-copy number. First, reference sample's genotype of the marker isconverted to an “A copy number” and “B copy number” according to TableIII:

TABLE III Genotype A copy number B copy number AA 2 0 AB 1 1 BB 0 2

Then, weighted linear regression is separately performed on (i) all theA signal values (versus A copy number) for all reference samples for themarker and (ii) all B signal values (versus B copy number) for all thereference samples for the marker. In one embodiment, weights are appliedbased on a predicted standard deviation for each copy number. Thepredicted standard deviation is determined from conducting linearregression on the observed standard deviations for the observedreference signals. The resulting predicted standard deviation for copynumber CNi (where i=0, 1, or 2) is noted herein by “pSD_(CNi)”. Then,when performing weighted linear regression on the observed signal valuesversus copy number, the observed value is weighted by multiplying it by1/(pSD_(CNi))² where pSD_(CNi) is the predicted standard deviationcorresponding to the copy number associated with the reference sample'sgenotype for the marker.

The above-referenced weighted linear regression is used on the A-signalvalues and corresponding A copy numbers to generate the Aintercept andAslope parameter values for the following A-model equation:

Asignal=Aintercept+Aslope*Acopynumber

And, the above-referenced weighted linear regression is used on theB-signal values and corresponding B copy numbers to generate theBintercept and Bslope parameter values for the following B-modelequation:

Bsignal=Bintercept+Bslope*Bcopynumber.

Using the above referenced A-model and B-model equations, step 2407predicts the A copy number (pAcopynumber) and B copy number(pBcopynumber) for an individual reference sample based on,respectively, the A signal value and B signal value (note, the A signalis a summarized signal using the median value of A signals for allreplicate probes and the B signal is a summarized signal using themedian value of B signals for all replicate probes) for a particularmarker. Therefore, pAcopynumber=(Asignal−Aintercept)/Aslope andpBcopynumber=(Bsignal−Bintercept)/Bslope. Using the predicted copynumber, the BAF is computed for each marker in each reference sample asfollows:

pBcopynumber/(pAcopynumber+pBcopynumber).

Step 2407 computes BAFs (based on the model from 2406) for known copynumber information from reference samples for each marker withsufficient reference information. Then, in step 2408, computed BAFs forthe same marker and genotype are compared to each other. Based on thiscomparison, markers for which the computed BAFs for AA genotypes havethe lowest standard deviation are selected for AA BAFs and markers forwhich the computed BAFs for BB genotypes have the lowest standarddeviation are selected for BB BAFs. Selection is done for later use inestimating fetal fraction based on signals from subject samples.

FIG. 5 illustrates subject sample processing method 2500. In oneembodiment, method 2500 is executed by subject sample processor 2300 ofFIG. 3. The particular steps shown in FIG. 4 are not necessarily allrequired in various alternative embodiments of the invention. Also, inalternatives, the particular steps and, in some cases, the order, can bevaried from that shown.

Steps 2501, 2502, 2503, 2504, and 2505 are substantially identical tosteps 2401, 2402, 2403, 2404, and 2405 of method 2400 of FIG. 4 andwon't be described in detail again here except to note that the steps inthe context of method 2500 are performed on data files obtained fromscanning subject (e.g. patient) samples obtained from pregnant females.Similar to step 2404, the results of step 2504 are summarized A-channelsignals (e.g. median signal value) for all replicate probes hybridizedto an A-allele for each marker for each subject sample (A-signals) andsummarized B-channel signals (e.g. median signal value) for allreplicate probes hybridized to a B-allele for each marker for eachsubject sample (B-signals).

Step 2505, like step 2405, obtains genotypes for each subject samplewith respect to each marker. Although a sample from a pregnant femalepresumably includes a fetal fraction, step 2505 determines an apparentgenotype of the mother or the genotype of the major subpopulation.

In some embodiments, several different subject maternal samplesprocessed on a same sample plate can be used to create reference signalsfor subsequent log ratio calculations. In such embodiments, step 2518sorts the summarized signals for all subject samples by genotype todetermine reference signals in the same manner as previously describedstep 2409 in FIG. 4. The only difference is that step 2518 uses currentsubject samples on a current sample plate to determine genotype-specificreference signals. However, in alternative embodiments that do notinclude step 2518, genotype-specific reference signals established for aset of reference samples previously analyzed on a different sample plate(e.g., as established by step 2409 of FIG. 4) can be used instead.

Step 2507 calculates a B-allele frequency (BAF) for markers identifiedin step 2408 of FIG. 4 for which the maternal genotype of the subjectsample, as determined in step 2505 of FIG. 5 is AA or BB. Prior tocalculating BAF, step 2507 converts A-signal values to predicted A copynumbers and B-signal values to predicted B copy numbers in the samemanner described in the context of step 2407 of FIG. 4, i.e., usingreference models such as the models determined at step 2406 of FIG. 4.

Step 2508 identifies markers for which the calculated BAF value meets orexceeds a threshold suggesting a fetal genotype of AB (i.e., differentthan mother's genotype, which is either AA or BB for each marker used instep 2508). In one embodiment, when the maternal genotype is AA for themarker, a BAF between about 0.015 and 0.2 suggests a fetal genotype thatis different than AA and triggers selection of the marker for use indetermining fetal fraction. Also, in such an embodiment, when thematernal genotype is BB for the marker, a BAF between about 0.8 and0.985 suggests a fetal genotype that is different than BB and triggersselection of the marker for use in determining fetal fraction. However,in alternative embodiments, these ranges might be varied or differentranges might be used for different markers without necessarily departingfrom the scope of this aspect of the present invention.

Step 2509 estimates fetal fraction using the selected markers.

Specifically, in one embodiment, fetal fraction is estimated for theselected markers as follows. For markers in which the mother's genotypeis AA, a fetal fraction α is estimated based on the equation BAF=α/2,i.e., α=2*BAF. The basis for this equation is the following: If themother is AA and the fetus is AB, Bcopynumber=a andAcopynumber=2*(1−α)+α=2−α. Therefore, Acopynumber+Bcopynumber=2−α+α=2.In a similar manner, if the mother's genotype is BB, a fetal fraction βis estimated based on the equation BAF=1−β/2. The basis for thisequation is the following: If the mother is BB and the fetus is AB,Bcopynumber=2(1−β)+β=2−β and AcopyNumber=β. Therefore,Acopynumber+Bcopynumber=2, and BAF=(2−β)/2=1−β/2.

Step 2510 determines whether the fetal fraction determined in step 2509is sufficiently high and/or sufficiently reliable for using thesubject's sample to screen for aneuploidy. In one embodiment, step 2510determines fetal faction sufficiency/reliability in two stages asfollows: First, it is determined if a sufficiently high enough fractionof markers for which the mother's genotype is AA has an α≥3% AND whethera sufficiently high enough fraction of markers for which the mother'sgenotype is BB has β≥3%. The use of a 3% threshold might vary based onthe noisiness of the particular assay utilized. However, in oneembodiment, it is assumed the noise level is such that some markers thatare AA (or BB) in both mother and fetus will show BAFs corresponding toa fetal fraction of more than 3%. Regarding the percentage of markersthat must meet the 3% threshold, in one embodiment, if less than 20% ofthe markers for which the mother is AA have α≥3% or if less than 9% ofthe markers for which the mother's genotype is AA have β≥3%, then thetest is rejected. The respective thresholds of 20% and 9% may be variedin alternative embodiments. In general, these are empirically determinedthresholds intended to optimize specificity and sensitivity, and theymay be varied to favor either of these performance measures, depending,in some cases, on assay noisiness.

If the sample passes the reliability thresholds such as, for example,those referenced above, the median α and median β across the relevantmarkers are, in one embodiment, used to estimate fetal fraction.Optionally, an additional reliability threshold is applied and thesample is rejected if a and β are not within a specified number ofpercentage points of each other for the sample to be accepted. In oneembodiment, the specified number of percentage points is 2-3% (e.g., ifα=4% and β=8%, the estimate is considered insufficiently reliable).However, in some embodiments, this additional reliability threshold isnot applied. Once α and β are established and considered acceptable, thesample is rejected if the values of α and β (for example, an average, ora weighted average) indicate a fetal fraction of less than 4%.

If the result of step 2510 is no, then step 2511 rejects the sample.Presumably, in most cases, another sample can be taken from the pregnantfemale for retesting, if desired, at a later date. In some alternativeembodiments, any rejection of a subject sample based on the variouscriteria reference above for reliability and/or sufficiency rejection isonly conditional and a conditionally rejected sample is stillpotentially considered if the relevant log ratios analyzed at step 2517(discussed further below) are sufficiently extreme to clearly indicateaneuploidy.

If the result of step 2510 is yes, then, preferably, step 2512 uses theestimated fetal fraction to update the thresholds used for the logratio. Step 2513 selects an appropriate reference signal based on thedetermined maternal genotype for the marker (e.g., for a particularmarker, selects one of the three reference signals shown in Table IIIabove corresponding to the maternal genotype) and determines a log ratioof the subject sample's signal for the relevant marker (summarized Asignal+summarized B signal) to the relevant selected reference signal.

Further processing is carried out in steps 2515, 2516, 2519, and 2514similar to that already describe above in the context of, respectively,steps 2412, 2413, 2415, and 2411 of FIG. 4.

Step 2517 analyzes the resulting normalized log ratios and callsaneuploidy if the ratios are above a threshold indicating an aberration.The theoretical log ratio for a normal sample is 0, while for a trisomysample with 5% fetal fraction it is Log 2((2*0.95+3*0.05)/2)=0.03562.However, in a particular implemented embodiment, an attenuation factorcan be determined empirically and considered. For example, in anembodiment with an attenuation factor of 0.8, a predicted log ratio forfetal trisomy when the fetal fraction is 5% is 0.8*0.03562. In one suchembodiment (i.e., with a 5% fetal faction, and an assay-relatedattenuation of 0.8, a threshold log ratio for calling aneuploidy mightbe between 0.02 and 0.03. However, alternative embodiments can use otherthresholds or other methods to compute attenuation.

Systems, apparatus, and methods described herein may be implementedusing a computer program product tangibly embodied in an informationcarrier, e.g., in a non-transitory machine-readable storage device, forexecution by a programmable processor; and the method steps describedherein, including one or more of the steps of the methods in FIG. 4, andFIG. 5 and alternative embodiments may be implemented using one or morecomputer programs that are executable by such a processor. A computerprogram is a set of computer program instructions that can be used,directly or indirectly, in a computer to perform a certain activity orbring about a certain result. A computer program can be written in anyform of programming language, including compiled or interpretedlanguages, and it can be deployed in any form, including as astand-alone program or as a module, component, subroutine, or other unitsuitable for use in a computing environment.

FIG. 6 shows an example of a computer system 2600, one or more of whichmay provide one or more of the components of, or alternatives tocomputer 2103 of FIG. 1. Computer system 2600 executes instruction codecontained in a computer program product 2660 (which may, for example, bethe computer program product 2104 of the embodiment of FIG. 1.) Computerprogram product 2660 comprises executable code in an electronicallyreadable medium that may instruct one or more computers such as computersystem 2600 to perform processing that accomplishes the exemplary methodsteps performed by the embodiments referenced herein. The electronicallyreadable medium may be any non-transitory medium that stores informationelectronically and may be accessed locally or remotely, for example viaa network connection. In alternative embodiments, the medium may betransitory. The medium may include a plurality of geographicallydispersed media each configured to store different parts of theexecutable code at different locations and/or at different times. Theexecutable instruction code in an electronically readable medium directsthe illustrated computer system 2600 to carry out various exemplarytasks described herein. The executable code for directing the carryingout of tasks described herein would be typically realized in software.However, it will be appreciated by those skilled in the art, thatcomputers or other electronic devices might utilize code realized inhardware to perform many or all the identified tasks without departingfrom the present invention. Those skilled in the art will understandthat many variations on executable code may be found that implementexemplary methods within the spirit and the scope of the presentinvention.

The code or a copy of the code contained in computer program product2660 may reside in one or more storage persistent media (not separatelyshown) communicatively coupled to system 2600 for loading and storage inpersistent storage device 2670 and/or memory 2610 for execution byprocessor 2620. Computer system 2600 also includes I/O subsystem 2630and peripheral devices 2640. I/O subsystem 2630, peripheral devices2640, processor 2620, memory 2610, and persistent storage device 2670are coupled via bus 2650. Like persistent storage device 2670 and anyother persistent storage that might contain computer program product2660, memory 2610 is a non-transitory media (even if implemented as atypical volatile computer memory device). Moreover, those skilled in theart will appreciate that in addition to storing computer program product2660 for carrying out processing described herein, memory 2610 and/orpersistent storage device 2670 may be configured to store the variousdata elements referenced and illustrated herein.

Those skilled in the art will appreciate computer system 2600illustrates just one example of a system in which a computer programproduct in accordance with an embodiment of the present invention may beimplemented. To cite but one example of an alternative embodiment,execution of instructions contained in a computer program product inaccordance with an embodiment of the present invention may bedistributed over multiple computers, such as, for example, over thecomputers of a distributed computing network.

While the present invention has been particularly described with respectto the illustrated embodiments, it will be appreciated that variousalterations, modifications and adaptations may be made based on thepresent disclosure and are intended to be within the scope of thepresent invention. While the invention has been described in connectionwith what are presently considered to be the most practical andpreferred embodiments, it is to be understood that the present inventionis not limited to the disclosed embodiments but, on the contrary, isintended to cover various modifications and equivalent arrangementsincluded within the scope of the underlying principles of the inventionas described by the various embodiments reference above and below.

1. A method for detecting a copy number in a fetus, comprising:obtaining a biological sample from a subject who is a pregnant female,the biological sample including nucleic acid of both maternal and fetalorigin containing a target nucleic acid sequence located on a firstchromosome, the target nucleic acid sequence containing a polymorphicsite for a single nucleotide polymorphism (SNP); generating a populationof nucleic acid fragments containing or derived from the target nucleicacid sequence; conducting a first assay comprising (a) contacting thepopulation of nucleic acid fragments with an oligonucleotide arraycontaining a first oligonucleotide probe configured to hybridize to thetarget nucleic acid sequence containing the polymorphic site of the SNP;and (b) detecting, using a detector, first signals indicatinghybridization of the oligonucleotide probe to one or more nucleic acidfragments of the population containing a first allelic variant (“Aallele”) of the SNP and second signals indicating hybridization of theoligonucleotide probe to one or more nucleic acid fragments of thepopulation containing a second allelic variant (“B allele”) of the SNP;and determining, using the first signals and the second signals, any oneor more of the following: (i) the copy number of the first chromosome inthe fetus; (ii) a fetal genotype for the SNP; (iii) a maternal genotypefor the SNP; and (iv) a fetal fraction of the sample.
 2. The method ofclaim 1, further comprising calculating the observed B-allele frequency(BAF) for the allelic variants of the SNP present in the sample.
 3. Themethod of claim 2, further including calculating the fetal fraction ofthe sample using the BAF.
 4. The method of claim 1, wherein thepolymorphic site of the SNP can be homozygous for the A allele (“AA”),homozygous for the B allele (“BB”) or heterozygous (“AB”).
 5. The methodof claim 4, wherein the detector has a first and a second detectionchannel, and the genotyping further includes detecting the first signalsin the first channel and the second signals in the second channel. 6.The method of claim 5, wherein the first signals in the first channelindicate the amount of A allele present in the nucleic acid populationand the second signals indicate the amount of B allele present atnucleic acid population.
 7. The method of claim 6, wherein determiningthe copy number of the first chromosome in the fetus comprisesdetermining a ratio of a first value to a second value.
 8. The method ofclaim 7, further comprising calculating the first value by normalizingand summarizing the first signals to obtain a first normalized andsummarized signal value, normalizing the second signals to obtain anormalized and summarized second signal value, and adding the normalizedand summarized first signal value to normalized and summarized secondsignal value to obtain the first value.
 9. The method of claim 4,further including determining a first maternal SNP genotype.
 10. Themethod of claim 8, wherein the second value is obtained by: conductingthe first assay on additional biological samples serving as referencesamples and identifying reference samples having an SNP genotypecorresponding to the first maternal SNP genotype; from conducting thefirst assay on the reference samples, obtaining first signals referencesignals detected in the first channel indicating an amount of A allelepresent in the polymorphic site of the SNP with respect to theadditional biological samples and obtaining second reference signalsindicating the amount of B allele present at the polymorphic site. 11.The method of claim 10, wherein the additional biological samples arefrom non-pregnant individuals.
 12. The method of claim 10, wherein theadditional biological samples include some samples from pregnant femalesand some samples from non-pregnant individuals.
 13. The method of claim10, wherein the additional biological samples include samples frompregnant females assayed on the same oligonucleotide array as thebiological sample from the subject pregnant female.
 14. The method ofclaim 1, wherein the nucleic acid sample includes maternal blood, plasmaor serum and the nucleic acid of both maternal and fetal origin includescell-free DNA (cfDNA).
 15. (canceled)
 16. The method of claim 1, whereinthe fetal DNA is no greater than 30% of total DNA in the nucleic acidsample.
 17. (canceled)
 18. The method of claim 1, wherein the fetal DNAis no greater than 20% of total DNA in the nucleic acid sample.
 19. Themethod of claim 1, wherein the fetal DNA is no greater than 15% of totalDNA in the nucleic acid sample.
 20. The method of claim 1, wherein thefetal DNA is no greater than 10% of total DNA in the nucleic acidsample.
 21. The method of claim 1, wherein the fetal DNA is no greaterthan 5% of total DNA in the nucleic acid sample.
 22. The method of claim1, wherein the fetal DNA is no greater than 15% and no less than 1% oftotal cell free DNA in the nucleic acid sample. 23.-54. (canceled)